In this paper we compare the predictive abilility of Stochastic Volatility (SV)models to that of volatility forecasts … implied by option prices. We develop anSV model with implied volatility as an exogeneous var able in the varianceequation … stochastic shocks incorporated in the SVXmodels. The out-of-sample volatility forecasts are evaluated against dailysquared …

process, at present this is not the case for the Heston stochastic volatility model, where the variance is modelled as a …

most important factor in reducing portfolio variance is the use of a flexible model for time varying volatility, rather … good on the present set of measures as the stochastic volatility models, with or without dynamic correlation. …

accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an … volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to … that time-varying volatility is only present in the a selection of idiosyncratic components while the coefficients driving …

, including market-based estimation of stochastic volatility models, the fine structure of equity-index option dynamics, leverage … and feedback effects in multifactor Wishart stochastic volatility for option pricing, option pricing with non …-Gaussian scaling and infinite-state switching volatility, stock return and cash flow predictability: the role of volatility risk, the …

index by univariate and multivariate long-memory stochastic volatility models.<P> Forthcoming in <I>Econometric Reviews</I>. …

conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain … variance, in the order of integration, in the short memory characteristics and in the volatility of volatility. …